Episode Transcript
[00:00:20] Speaker A: Welcome to Bass by Bass, the papercast that brings genomics to you wherever you are. Thanks for listening and don't forget to follow and rate us in your podcast. Appreciate.
So imagine you are playing a high stakes game of Whack a mole.
[00:00:32] Speaker B: Okay, that can picture that, right?
[00:00:34] Speaker A: You're standing there, mallet in hand, just waiting for the mole to pop up.
But this isn't your standard arcade game. In this version, the mole somehow knows exactly which mallet you're going to use next.
[00:00:46] Speaker B: Like it's a reading your mind or something.
[00:00:49] Speaker A: Exactly. Maybe you're going to use a standard wooden hammer or, you know, a metal baseball bat, or maybe you just suddenly switch it up and throw a water balloon.
[00:00:58] Speaker B: Right. Totally different types of attacks.
[00:01:00] Speaker A: Yeah, and in a normal game, the mole reacts after being hit. But what if instead of adapting after the fact, some rare moles are already wearing like a tiny rain jacket or a metal helmet? They're perfectly prepared to survive strikes they have never even seen before.
[00:01:15] Speaker B: Oh, wow. Okay. So in the world of oncology, those moles are rare cancer cells.
[00:01:20] Speaker A: You got it. What really happens when a cancer cell is inherently equipped to dodge an entire arsenal of distinct therapies? Okay, let's unpack this.
[00:01:30] Speaker B: Today we celebrate the work of Dylan L. Schaff, Sydney M. Shaffer and their collaborating teams at the University of Pennsylvania, Johns Hopkins and other leading institutions who have advanced our understanding of multi treatment
[00:01:42] Speaker A: cancer resistance, which is such a crucial area of research right now.
[00:01:46] Speaker B: It really is. They published these findings in the journal cell genomics in 2026, offering us a totally new lens on how we view tumor evasion. Yeah, we are moving away from looking at resistance as a purely reactive process.
[00:02:00] Speaker A: Right. And instead seeing it as a pre existing condition within certain rare cells.
[00:02:04] Speaker B: Exactly. Which represents a massive shift in how we approach treating the disease.
[00:02:09] Speaker A: Because, I mean, clinically speaking, tumors are just famously stubborn.
[00:02:13] Speaker B: Oh, absolutely.
[00:02:13] Speaker A: If you know anyone who has navigated cancer treatment, you know that patients are often given complex CN sequences of therapies or, you know, combinations of different toxic drugs to try and cover all the bases.
[00:02:23] Speaker B: Throwing everything at the wall to see what sticks.
[00:02:25] Speaker A: Right. But tragically, some patients still develop resistance to absolutely all of them. The cancer simply keeps.
Well, it just keeps finding a way to survive.
[00:02:35] Speaker B: And historically, the scientific paradigm has been to assume this resistance comes primarily from
[00:02:41] Speaker A: genetic mutations, like a physical change in the DNA code.
[00:02:44] Speaker B: Right. The prevailing thought was that a cell acquires a random typo in its DNA that miraculously allows it to survive the drug. Or alternatively, we thought cells dynamically adapted their inner molecular workings, you know, under the immense stress of the treatment itself.
[00:03:02] Speaker A: So they change during the attack.
[00:03:03] Speaker B: Exactly. But recently, a non genetic angle has emerged. The scientific community is realizing that differences in gene expression, meaning which specific genes are turned on or off in a cell at any given moment, can actually
[00:03:15] Speaker A: dictate resistance totally independent of any underlying change to the DNA code itself.
[00:03:20] Speaker B: Yes, but trying to study that initial gene expression creates a massive methodological paradox for researchers.
[00:03:27] Speaker A: Oh, totally. Because if you want to know what a cell looked like before it became resistant, you have to examine it before you treat it.
[00:03:33] Speaker B: Right.
[00:03:33] Speaker A: But the very act of dropping toxic chemotherapy drugs onto a cell, that drastically alters its gene expression, it changes the
[00:03:41] Speaker B: very thing you're trying to observe.
[00:03:42] Speaker A: Yeah, it's like. It's like trying to investigate a crime scene to figure out how a fire started while the building is actively burning down around you.
[00:03:51] Speaker B: That's a great way to put it. The evidence you need is literally going up in smoke.
[00:03:54] Speaker A: Exactly.
[00:03:55] Speaker B: This raises an important question. How can we look back in time to see what a surviving cell looked like before the treatment?
[00:04:03] Speaker A: Because standard molecular analysis destroys that initial pre treatment baseline.
[00:04:09] Speaker B: Exactly. But the researchers came up with a brilliant workaround for this deep dive. They combined a technique called clonal tracing with single cell RNA sequencing, or CRNA SEQ for short. Right. And we can think of this like giving a unique microscopic tracking number to thousands of identical twins.
[00:04:27] Speaker A: Okay, I like this analogy.
[00:04:28] Speaker B: You tag them, you send them off to different extreme survival camps, and then you just wait to see who makes it out alive.
[00:04:34] Speaker A: And when you check the tracking numbers of the survivors, you know exactly which original family they came from.
[00:04:40] Speaker B: Precisely. And to actually get those tracking numbers into the cells, they use the lentivirus.
[00:04:45] Speaker A: Ah, right. A lentiviral approach is crucial.
[00:04:49] Speaker B: Here it is. A lentivirus is essentially a virus that has been hollowed out and turned into, well, a microscopic delivery truck.
[00:04:57] Speaker A: So instead of delivering a disease payload, they packed it with unique DNA barcodes.
[00:05:02] Speaker B: Exactly. When they infect the cells, the virus inserts that unique barcode directly into the cell's genome. And what makes this so powerful is that every time that cell divides, it copies the barcode.
[00:05:13] Speaker A: So it passes the tracking number down to its descendants.
[00:05:16] Speaker B: Right. And the researchers introduced this barcode library into a specific type of melanoma cell line. This, the WM989V600E BRAF line.
[00:05:26] Speaker A: And they did this on an absolutely massive scale, didn't they?
[00:05:28] Speaker B: Oh, yeah, huge.
[00:05:30] Speaker A: I was looking at the methodology, and they used Fluorescence activated cell sorting to isolate exactly 350,000 uniquely barcoded cells.
[00:05:39] Speaker B: It's incredible volume.
[00:05:41] Speaker A: Right. And from there, they let those cells multiply, expanding them for about six doublings. So one barcoded cell becomes two to become four.
[00:05:48] Speaker B: Until you have a whole microscopic colony sharing the exact same tracking number.
[00:05:52] Speaker A: Yeah, and that expansion population of about 23 million cells.
[00:05:57] Speaker B: Right, and because they share a barcode, we know for a fact they share a lineage. They are clonal copies of each other.
[00:06:04] Speaker A: So what did they do with those 23 million cells?
[00:06:07] Speaker B: Well, they took this massive population and divided it. They kept an untreated control group and then split the rest across 12 different treatment arms.
[00:06:15] Speaker A: 12? Yeah.
[00:06:16] Speaker B: This consisted of two replicates for six highly diverse, extremely harsh treatments. These were the survival camps you mentioned, man.
[00:06:23] Speaker A: And to really test these cells, they didn't just use one type of chemical. They threw the absolute worst case biological scenarios at them.
[00:06:31] Speaker B: They really did. First, they used targeted clinical inhibitors.
[00:06:35] Speaker A: Right. They used dobrofenib, which specifically targets a mutation in the BRAF protein, and trementinib,
[00:06:41] Speaker B: which inhibits the MEK protein.
[00:06:43] Speaker A: And both of these drugs are designed to physically block a specific cell. Cellular signaling highway. Right, the one that melanoma relies on to grow uncontrollably.
[00:06:52] Speaker B: Exactly. But they didn't stop there. Following those targeted inhibitors, they introduced biological
[00:06:57] Speaker A: selective stressors to kind of chemically mimic the suffocating toxic environment found deep inside a solid tumor in the human body.
[00:07:05] Speaker B: Right, because as tumors grow, their blood supply often just can't keep up. So to simulate this, the team used cobalt chloride or CoCl2, to chemically induce
[00:07:14] Speaker A: hypoxia, essentially starving the cells of oxygen.
[00:07:17] Speaker B: Yes, and they also used highly acidic media to simulate extracellular acidosis, pushing the cell's delicate PH balance right to the brink.
[00:07:26] Speaker A: And finally, they brought in the heavy chemotherapeutics.
[00:07:29] Speaker B: The really toxic stuff.
[00:07:30] Speaker A: Yeah, they used cisplatin, which literally binds to and causes physical breaks in the cell's DNA strands. Right. And doxorubicin, which inhibits an enzyme called poisonerase. And if taumerase is blocked, the cell cannot unwind its DNA to replicate, meaning
[00:07:47] Speaker B: it physically cannot divide.
[00:07:49] Speaker A: So that is six totally different mechanisms of attack. You have targeted signaling blocks, oxygen starvation, acid baths, and DNA shredders.
[00:07:58] Speaker B: Which brings us to the RNA time machine.
[00:08:00] Speaker A: Oh, this is the best part.
[00:08:01] Speaker B: Right. So, before exposing the cells to these six harsh conditions, the researchers took a sample of the untreated cells and ran single cell RNA sequencing.
[00:08:10] Speaker A: And this technique captures all the messenger RNA a cell is currently reading.
[00:08:14] Speaker B: Exactly. It gives the researchers a complete snapshot of the molecular blueprint showing exactly which genes are turned on and off for every single barcode family before any stress was ever applied.
[00:08:24] Speaker A: And then what, A whole month later, they sequenced the barcodes of the rare cells that actually survived those survival camps.
[00:08:30] Speaker B: You got it. By matching the barcodes of the final hardened survivors back to that pre treatment RNA snapshot, they could see exactly what those specific cells were doing differently, but before the chemical warfare even started.
[00:08:43] Speaker A: So cool. So what did the data actually show?
[00:08:46] Speaker B: Well, the first major observation from mapping those barcodes was that resistance is highly heritable over those six doublings.
[00:08:53] Speaker A: Meaning if a clone survived in one replicate of a drug, its identical cousins almost always survived in the second replicate.
[00:09:00] Speaker B: Right.
But looking at how they survived across the different drugs revealed a really striking divide between what we can call specialists and generalists.
[00:09:10] Speaker A: Okay, tell me about the specialists first.
[00:09:12] Speaker B: So about 20 to 40% of the top resistant clones were specialists.
This means they possessed a pre existing gene expression state that allowed them to survive one and only one specific type of treatment.
[00:09:25] Speaker A: Which is exactly what we have traditionally expected in cancer biology.
[00:09:28] Speaker B: Right, but the generalists completely flipped the script on how we view tumor resilience.
Out of hundreds of thousands of original clones, the team found 11 extremely rare clones that were captured in the top 10% of survivors across all six treatments.
[00:09:43] Speaker A: Wait, all six?
[00:09:44] Speaker B: All six? These specific cells were inherently multi treatment resistant.
[00:09:48] Speaker A: So they possessed an internal state that made them virtually invincible to targeted therapy, chemotherapy, oxygen deprivation, and acid all at once.
[00:09:58] Speaker B: Exactly. And tracing those 11 generalist barcodes back to the pre treatment data revealed heavily overlapping gene expression signatures.
[00:10:06] Speaker A: So they shared a specific profile.
[00:10:08] Speaker B: Yes. Two genes in particular, CD44 and FN1, were highly expressed in the clones that later went on to resist dabrafenib, Trematinib, and the hypoxia mimic COCL2.
[00:10:20] Speaker A: Okay, and FN1 stands for fibronectin 1, right?
[00:10:23] Speaker B: Right. It is a protein that cells use to interact with the extracellular matrix around them.
It essentially helps them anchor to their environment and communicate with neighboring cells.
[00:10:32] Speaker A: So the untreated cells destined to survive had already dialed up the volume on these specific genes they had. Wait, so is having high CD44amagical, impenetrable shield against cancer drugs, or is it just a red flag indicating the cell happens to be tough?
[00:10:46] Speaker B: That is the million dollar question.
[00:10:48] Speaker A: Because there must be some kind of biological cost to maintaining that super survivor state. Right. Or else evolution would just Ensure every single cancer cell look like that.
[00:10:57] Speaker B: Exactly. The researchers asked that exact question about causation versus correlation. They actually ran a validation experiment where they physically sorted the melanoma cells into two distinct groups.
[00:11:09] Speaker A: Based on the CD44 expression.
[00:11:11] Speaker B: Yes. Those naturally high in CD44 and those low in CD44. And as the clonal tracing predicted, the CD44 high cells were vastly more resistant to the subsequent treatments.
[00:11:23] Speaker A: But they needed to test if CD44 was the shield itself, right?
[00:11:27] Speaker B: Right. So they used a peptide inhibitor called Angstrom 6.
This inhibitor is designed to block CD44 from interacting with its normal binding partners on the outside of the cell.
[00:11:36] Speaker A: Okay, so if CD44 was the functional shield blocking, it should have immediately sensitized the cells to the drug debrefenib.
[00:11:43] Speaker B: Precisely.
[00:11:44] Speaker A: Let me guess. Taking away the CD44 interaction didn't stop them from surviving.
[00:11:48] Speaker B: You guessed it. The Angstrom 6 inhibitor did not consistently sensitize them to the treatment. Which strongly indicates that CD44 is acting more as a prominent marker of a resistance state, rather than being the direct physical mechanism of the shield.
[00:12:01] Speaker A: It is the red flag on the tough cell.
[00:12:03] Speaker B: Exactly. And the biological cost you mentioned earlier likely comes from the massive energy requirements of the actual mechanism keeping them alive. Which turned out to be hyperactive lysosomes.
[00:12:14] Speaker A: Lysosomes are. Oh, I remember from biology class that those are essentially the cellular garbage disposals.
[00:12:19] Speaker B: That's a perfect description.
[00:12:21] Speaker A: They're like small compartments inside the cell filled with highly acidic enzymes that just break down waste and cellular debris.
[00:12:27] Speaker B: Right, and the CD44 high cells had highly elevated expression of lysosomal pathway genes.
Specifically genes like SRGN and VMP1.
[00:12:37] Speaker A: Okay, what do those do?
[00:12:38] Speaker B: Well, SRGN produces a protein that helps package materials inside these acidic compartments.
And VMP1 is heavily involved in forming the cellular vesicles that transport waste to the lysosomes.
[00:12:49] Speaker A: So they basically built a more robust trash transport system.
[00:12:53] Speaker B: Yeah, and to prove it, they used a special dye called lysotracker that literally lights up under a microscope in the presence of active lysosomes.
[00:13:02] Speaker A: Oh, that's clever.
[00:13:04] Speaker B: Right, and they proved the CD44 high cells had hyperactive garbage disposals even before any treatment was applied.
[00:13:11] Speaker A: That is wild. So the theory is that these cells are surviving because their disposal systems are just in overdrive.
[00:13:18] Speaker B: Exactly. They are actively sequestering the toxic cancer
[00:13:21] Speaker A: drugs, pulling them into these highly acidic lysosome compartments, and then degrading the chemical structure of the drug before it can ever reach its target.
[00:13:30] Speaker B: Inside the cell, they're essentially swallowing the poison and digesting it into harmless waste.
[00:13:34] Speaker A: That perfectly explains the generalists superstate. But does a cell facing Dabrofendum have to use this specific garbage disposal state to live? Here's where it gets really interesting.
[00:13:45] Speaker B: Because biology always finds multiple paths to survival.
[00:13:48] Speaker A: Always.
[00:13:49] Speaker B: The researchers wanted to see if totally different starting states could lead to the exact same destination of survival.
[00:13:55] Speaker A: So how did they test that?
[00:13:56] Speaker B: To analyze this, they utilized a complex computational technique called consensus non negative matrix factorization, or CNMF clustering.
[00:14:06] Speaker A: Okay, let's break that down, because CNMF sounds incredibly dense.
[00:14:10] Speaker B: It is a bit of a mouthful.
[00:14:12] Speaker A: Is it accurate to think of CNMF like looking at the listening habits of millions of Spotify users?
[00:14:18] Speaker B: How do you mean?
[00:14:19] Speaker A: Like, instead of just looking at one single song a user plays, the algorithm finds hidden playlists. It identifies coordinated programs of gene expression. Hundreds of genes that always seem to activate together in the background.
[00:14:32] Speaker B: That is a brilliant way to conceptualize it.
[00:14:34] Speaker A: Yes.
[00:14:35] Speaker B: By finding those hidden genetic playlists, the algorithm revealed that cells starting in totally different initial states could become resistant to the exact same drug. Deborah, by taking entirely different molecular paths.
[00:14:46] Speaker C: Wow.
[00:14:46] Speaker A: Okay, what were the paths?
[00:14:48] Speaker B: They found two main starting states. First, there were what they called differentiated clones.
These cells had high expression of typical melanocytic markers like mlan, which is a protein involved in melanin production, and mitf, which acts as a master regulator of melanocyte development.
[00:15:03] Speaker A: So before treatment, these just look like standard run of the mill melanoma cells.
[00:15:08] Speaker B: Exactly.
[00:15:08] Speaker A: And how did those standard looking cells manage to survive a targeted drug like Deborah Thinib, which is literally designed to block their main BRAF growth pathway.
[00:15:19] Speaker B: They survived by upregulating a totally different signaling pathway known as kras.
[00:15:24] Speaker A: Ah, okay.
[00:15:25] Speaker B: But by activating the KRAS pathway, the cell essentially sends an alternative keep growing signal to the nucleus. This completely bypasses the blocked bras proteins.
[00:15:35] Speaker A: It is a biological detour around the drug's roadblock.
[00:15:38] Speaker B: Perfect way to describe it.
[00:15:39] Speaker A: But then you have the second group, right? The mesenchymal clones.
[00:15:42] Speaker B: Yes.
[00:15:42] Speaker A: These are the cells that started out high in our Red Flag CD44 and FN1. They obviously didn't take the KRAS Detour.
[00:15:49] Speaker B: No, they survived by turning up the volume on entirely different programs. Specifically, they upregulated epithelial mesenchymal transition, or
[00:15:57] Speaker A: EMT pathways, which is a fascinating process where a cell fundamentally changes its shape. Right. It loses its rigid adhesion to neighboring cells and becomes much more mobile and Resilient to external stress.
[00:16:08] Speaker B: Exactly. And alongside emt, they also upregulated oxidative phosphorylation.
[00:16:13] Speaker A: Okay, and that's a highly efficient way for cells to generate large amounts of energy using oxygen inside their mitochondria. Right, so you have two different types of cells facing the exact same targeted threat. And they both survive, but by pulling entirely different molecular levers inside their cellular machinery.
[00:16:32] Speaker B: One uses a signaling detour and the other sheepshifts and cranks up its energy production.
[00:16:36] Speaker A: So did I remember reading the population data in the deep dive sources. Wait, a 33 fold expansion compared to a 1.6 fold expansion?
[00:16:44] Speaker B: Yes.
[00:16:45] Speaker A: That means the mesenchymal clones aren't just surviving the targeted therapy, they are aggressively thriving in it.
[00:16:51] Speaker B: The disparity in their survival efficiency is really stark. During the prolonged treatment period, the population of the mesenchymal clones expanded by 33.2 times.
[00:17:01] Speaker A: That's huge.
[00:17:02] Speaker B: Meanwhile, the differentiated clones, you know, the ones relying on the Kras signaling detour. They only managed to increase their population by 1.6 times.
[00:17:11] Speaker A: Wow. So one group is grudgingly holding on, barely surviving the chemical assault, while the other group is multiplying exponentially while bathed in toxic drugs.
[00:17:20] Speaker B: Exactly. If we connect this to the bigger picture.
[00:17:23] Speaker A: Yeah, let's do that.
[00:17:24] Speaker B: The clinical implications of this are profound.
If we know that tumors naturally harbor these rare pre existing generalists that are capable of surviving almost anything we throw
[00:17:35] Speaker A: at them, and if we know they use distinct transcriptional pathways like hyperactive lysosomes or EMT to achieve that survival, then
[00:17:44] Speaker B: we can completely change how we treat the disease. Instead of just reacting to resistance after a tumor starts growing again, we can extract these targetable gene expression states to eliminate multi treatment resistance before it even starts.
[00:17:57] Speaker A: Because if you sequence a patient's tumor and see it has a high population of these CD44 high cells with hyperactive garbage disposals, you wouldn't just give them a standard targeted drug that is inevitably going to get chewed up and digested.
[00:18:09] Speaker B: Right. It would be pointless.
[00:18:10] Speaker A: You would need to proactively target the garbage disposal system itself. Or, you know, target the specific oxidative phosphorylation energy pathways they rely on alongside the traditional therapy. You have to take away their shield first.
[00:18:24] Speaker B: Yes. And the methodology itself, using lentiviral clonal tracing combined with single cell RNA sequencing, could be deployed far beyond just these six drugs.
[00:18:34] Speaker A: Oh, totally. We could use this exact framework to study resistance against cutting edge immunotherapies like
[00:18:41] Speaker B: checkpoint inhibitors or cancer vaccines, or even Car T cell therapy.
[00:18:44] Speaker C: Yeah.
[00:18:45] Speaker B: We could look at how well different pre existing cellular states absorb targeted drug delivery systems like nano carriers.
[00:18:51] Speaker A: The applications are really limited only by the treatments we wish to test.
It feels like we are finally getting a look at the opponent's playbook before the game even begins. But we absolutely need to responsibly outline the boundaries of this specific study. Of course this is incredibly exciting paradigm shifting data, but it was all done in vitro, meaning in a plastic. Plastic petri dish in a laboratory. And it relied on a single established melanoma cell line. The WM9889 line.
[00:19:18] Speaker B: A vital point to make. While the researchers went to great lengths to use things like cobalt chloride in acidic media to mimic the severe stress of a tumor, a plastic petri dish severely lacks the complexity of a true in vivo tumor microenvironment.
[00:19:34] Speaker A: Right. Because inside a human body, a solid tumor is a chaotic three dimensional ecosystem system.
[00:19:40] Speaker B: Exactly. There are constant dynamic interactions with the patient's attacking immune cells. There are structural stromal components like collagen and blood vessels.
[00:19:48] Speaker A: And there are true shifting metabolic gradients where oxygen and acid levels change millimeter by millimeter.
[00:19:54] Speaker B: Right. So a cell that looks and acts like a super survivor when it is sitting flat in a plastic dish might behave very differently when it is surrounded by a swarm of attacking key cells, fluctuating blood supply and physical tissue barriers.
[00:20:07] Speaker A: The plastic dish is a highly controlled environment which is strictly necessary to isolate these specific genetic variables and prove causation.
[00:20:14] Speaker B: But it isn't the whole picture of human disease. Future studies must use patient derived tumor models and complex in vivo systems to validate these markers.
[00:20:24] Speaker A: We need to see if CD44 acts as the same reliable red flag in a living breathing organism as it does in the lab.
[00:20:30] Speaker B: Exactly. But what's fascinating here is that despite those in vitro limitations, the underlying ability to look back in time and definitively link a cell's initial molecular state to its final fate across multiple treatments is a massive leap forward for oncology.
[00:20:47] Speaker A: It really is.
[00:20:47] Speaker B: To summarize the findings, rare cancer cells possess pre existing gene expression states marked by genes like CD44 that grant them generalist resistance to multiple diverse treatments simultaneously.
Furthermore, by mapping a cell's initial transcriptional state, we can predict the divergent molecular pathways it will take to survive. Proving that tumors possess multiple blueprints for evasion.
[00:21:10] Speaker A: What does this mean for the future of personalized medicine? When we can read a tumor's generalist playbook before administering the very first dose of therapy?
[00:21:18] Speaker B: That is the Big Question this episode
[00:21:20] Speaker A: was based on an Open Access article under the CCBY 4.0 license. You can find a direct link to the the paper and the license in our episode description. If you enjoyed this, follow or subscribe in your podcast app and leave a five star rating. If you'd like to support our work, use the donation link in the description. Now. Stay with us for an original track created especially for this episode and inspired by the article you've just heard about. Thanks for listening and join us next time as we explore more science base by base.
[00:22:04] Speaker C: In the quiet split of a single line Some shadows grow where the lights don't shine before the first dose before the alarm a secret script is already on Barcodes on heartbeats Patterns in the noise Rare little rebels making their choice if you listen close you can hear a star resistance Written like a spark oh it's built before the battle Hiding in plain view Same old body but the cells are too when the pressure rises they slip right through Premade survivors in a different groove.
1 state run CD 44 high feeding the firm is where the hard things hide Lysosomes humming Auto faggy tight turn in the dark and just staying alive different drugs, different storms S dread in the air Heritable whispers that clones learn to wear Map the beginning and you map the end Find the first note and you might bend yeah, it's built before the battle Hiding in plain view not just chance there's a tail coming through Track that signal, break that signal Loop caster air resistance state before it moves.
